Efficient phase unwrapping architecture for digital holographic microscopy

Digital holographic approaches to the detection and characterization of microplastics in water environments

Microplastic (MP) pollution is seriously threatening the environmental health of the world, which has accelerated the development of new identification and characterization methods. Digital holography (DH) is one of the emerging tools to detect MPs in a high-throughput flow. Here, we review advances in MP screening by DH. We examine the problem from both the hardware and software viewpoints. Automatic analysis based on smart DH processing is reported by highlighting the role played by artificial intelligence for classification and regression tasks. In this framework, the continuous development and availability in recent years of field-portable holographic flow cytometers for water monitoring also is discussed.

Beyond conventional microscopy: Observing kidney tissues by means of fourier ptychography

Kidney microscopy is a mainstay in studying the morphological structure, physiology and pathology of kidney tissues, as histology provides important results for a reliable diagnosis. A microscopy modality providing at same time high-resolution images and a wide field of view could be very useful for analyzing the whole architecture and the functioning of the renal tissue. Recently, Fourier Ptychography (FP) has been proofed to yield images of biology samples such as tissues and in vitro cells while providing high resolution and large field of view, thus making it a unique and attractive opportunity for histopathology. Moreover, FP offers tissue imaging with high contrast assuring visualization of small desirable features, although with a stain-free mode that avoids any chemical process in histopathology. Here we report an experimental measuring campaign for creating the first comprehensive and extensive collection of images of kidney tissues captured by this FP microscope. We show that FP microscopy unlocks a new opportunity for the physicians to observe and judge renal tissue slides through the novel FP quantitative phase-contrast microscopy. Phase-contrast images of kidney tissue are analyzed by comparing them with the corresponding renal images taken under a conventional bright-field microscope both for stained and unstained tissue samples of different thicknesses. In depth discussion on the advantages and limitations of this new stain-free microscopy modality is reported, showing its usefulness over the classical light microscopy and opening a potential route for using FP in clinical practice for histopathology of kidney.

Region-referenced phase unwrapping architecture for digital holographic microscopy

This work presents a novel hardware phase-unwrapping architecture for digital holographic microscopy. The architecture is based on an iterative region-referenced algorithm because of its simplicity and effectiveness for phase unwrapping. The architecture therefore consumes fewer hardware resources for very large-scale integration implementation. In addition, a novel data reuse scheme is adopted for reducing the memory bandwidth required by the architecture. The architecture can then have fast computation speed for the iterative operations. The architecture has been implemented by field programmable gate array. It acts as a hardware accelerator in an embedded system developed by a network-on-chip platform for performance measurement. The superiorities of the proposed architecture have been confirmed by the experiments.

Dynamic quantitative phase imaging for biological objects using a pixelated phase mask

This paper describes research in developing a dynamic quantitative phase imaging microscope providing instantaneous measurements of dynamic motions within and among live cells without labels or contrast agents. It utilizes a pixelated phase mask enabling simultaneous measurement of multiple interference patterns derived using the polarization properties of light to track dynamic motions and morphological changes. Optical path difference (OPD) and optical thickness (OT) data are obtained from phase images. Two different processing routines are presented to remove background surface shape to enable quantification of changes in cell position and volume over time. Data from a number of different moving biological organisms and cell cultures are presented.